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Statistical guarantees for the EM algorithm: From population to sample-based analysis

9 August 2014

Sivaraman Balakrishnan

Martin J. Wainwright

Bin Yu

ArXiv (abs)PDF HTML

Papers citing "Statistical guarantees for the EM algorithm: From population to sample-based analysis"

50 / 265 papers shown

Title
Optimal Subspace Estimation Using Overidentifying Vectors via Generalized Method of Moments Jianqing Fan Yiqiao Zhong 96 10 0 08 May 2018
Gradient Descent with Random Initialization: Fast Global Convergence for Nonconvex Phase Retrieval Yuxin Chen Yuejie Chi Jianqing Fan Cong Ma 232 249 0 21 Mar 2018
Hidden Integrality and Semi-random Robustness of SDP Relaxation for Sub-Gaussian Mixture Model Yingjie Fei Yudong Chen 139 5 0 17 Mar 2018
Sharp oracle inequalities for stationary points of nonconvex penalized M-estimatorsIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2018 A. Elsener Sara van de Geer 160 12 0 27 Feb 2018
Functional Gradient Boosting based on Residual Network PerceptionInternational Conference on Machine Learning (ICML), 2018 Atsushi Nitanda Taiji Suzuki 161 28 0 25 Feb 2018
Learning Mixtures of Linear Regressions with Nearly Optimal Complexity Yuanzhi Li Yingyu Liang 198 78 0 22 Feb 2018
Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms Ashok Vardhan Makkuva Sewoong Oh Sreeram Kannan Pramod Viswanath MoE 159 21 0 21 Feb 2018
Robust Estimation via Robust Gradient Estimation Adarsh Prasad A. Suggala Sivaraman Balakrishnan Pradeep Ravikumar 268 223 0 19 Feb 2018
Non-convex Optimization for Machine Learning Prateek Jain Purushottam Kar 322 502 0 21 Dec 2017
On the nonparametric maximum likelihood estimator for Gaussian location mixture densities with application to Gaussian denoising Sujayam Saha Adityanand Guntuboyina 153 56 0 06 Dec 2017
Clustering Semi-Random Mixtures of Gaussians Pranjal Awasthi Aravindan Vijayaraghavan 138 12 0 23 Nov 2017
Parameter Estimation in Gaussian Mixture Models with Malicious Noise, without Balanced Mixing Coefficients Jing Xu Jakub Mareˇcek 109 5 0 21 Nov 2017
Alternating minimization for dictionary learning: Local Convergence Guarantees Niladri S. Chatterji Peter L. Bartlett 168 28 0 09 Nov 2017
On Learning Mixtures of Well-Separated Gaussians O. Regev Aravindan Vijayaraghavan 238 75 0 31 Oct 2017
An Expectation Maximization Framework for Yule-Simon Preferential Attachment Models Lucas Roberts Denisa Roberts 61 1 0 23 Oct 2017
Estimating a network from multiple noisy realizations Can M. Le Keith Levin Elizaveta Levina 184 38 0 13 Oct 2017
Reliable Clustering of Bernoulli Mixture Models Amir Najafi Abolfazl Motahari Hamid R. Rabiee 92 3 0 05 Oct 2017
Maximum likelihood estimation of the Latent Class Model through model boundary decomposition E. Allman H. Cervantes R. Evans Serkan Hocsten Kaie Kubjas Daniela Lemke J. Rhodes Piotr Zwiernik 214 15 0 04 Oct 2017
Community Recovery in Hypergraphs Kwangjun Ahn Kangwook Lee Changho Suh 123 35 0 12 Sep 2017
Learning Mixture of Gaussians with Streaming Data Aditi Raghunathan Ravishankar Krishnaswamy Prateek Jain 154 8 0 08 Jul 2017
An Alternative to EM for Gaussian Mixture Models: Batch and Stochastic Riemannian OptimizationMathematical programming (MP), 2017 Reshad Hosseini S. Sra 117 68 0 10 Jun 2017
Convergence Analysis of Gradient EM for Multi-component Gaussian Mixture Bowei Yan Mingzhang Yin Purnamrita Sarkar 147 1 0 23 May 2017
Solving (most) of a set of quadratic equalities: Composite optimization for robust phase retrieval John C. Duchi Feng Ruan 165 178 0 05 May 2017
Estimating the Coefficients of a Mixture of Two Linear Regressions by Expectation Maximization Jason M. Klusowski Dana Yang W. Brinda 143 44 0 26 Apr 2017
Speeding Up Latent Variable Gaussian Graphical Model Estimation via Nonconvex OptimizationsNeural Information Processing Systems (NeurIPS), 2017 Pan Xu Jian Ma Quanquan Gu CML 114 25 0 28 Feb 2017
Structured signal recovery from quadratic measurements: Breaking sample complexity barriers via nonconvex optimizationIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2017 Mahdi Soltanolkotabi 155 107 0 20 Feb 2017
Rate Optimal Estimation and Confidence Intervals for High-dimensional Regression with Missing CovariatesJournal of Multivariate Analysis (J. Multivar. Anal.), 2017 Yining Wang Jialei Wang Sivaraman Balakrishnan Aarti Singh 162 9 0 09 Feb 2017
Maximum likelihood estimation of determinantal point processes Victor-Emmanuel Brunel Ankur Moitra Philippe Rigollet John C. Urschel 200 11 0 23 Jan 2017
Statistical and Computational Guarantees of Lloyd's Algorithm and its Variants Yu Lu Harrison H. Zhou 424 123 0 07 Dec 2016
Simultaneous Clustering and Estimation of Heterogeneous Graphical Models Botao Hao W. Sun Yufeng Liu Guang Cheng 236 87 0 28 Nov 2016
On the Convergence of the EM Algorithm: A Data-Adaptive Analysis Chong Wu Can Yang Hongyu Zhao Ji Zhu 188 19 0 02 Nov 2016
Convergence rate of stochastic k-means Cheng Tang C. Monteleoni 156 26 0 16 Oct 2016
STORE: Sparse Tensor Response Regression and Neuroimaging Analysis W. Sun Lexin Li 209 97 0 15 Sep 2016
Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences Chi Jin Yuchen Zhang Sivaraman Balakrishnan Martin J. Wainwright Sai Li 191 140 0 04 Sep 2016
Ten Steps of EM Suffice for Mixtures of Two Gaussians C. Daskalakis Christos Tzamos Manolis Zampetakis 599 128 0 01 Sep 2016
Global analysis of Expectation Maximization for mixtures of two GaussiansNeural Information Processing Systems (NeurIPS), 2016 Ji Xu Daniel J. Hsu A. Maleki 430 131 0 26 Aug 2016
Solving a Mixture of Many Random Linear Equations by Tensor Decomposition and Alternating Minimization Xinyang Yi Constantine Caramanis Sujay Sanghavi 117 62 0 19 Aug 2016
A Tight Convex Upper Bound on the Likelihood of a Finite MixtureInternational Conference on Pattern Recognition (ICPR), 2016 Elad Mezuman Yair Weiss 61 1 0 18 Aug 2016
Statistical Guarantees for Estimating the Centers of a Two-component Gaussian Mixture by EM Jason M. Klusowski W. Brinda 128 20 0 07 Aug 2016
Covariate Regularized Community Detection in Sparse GraphsJournal of the American Statistical Association (JASA), 2016 Bowei Yan Purnamrita Sarkar 295 61 0 10 Jul 2016
Finding Low-Rank Solutions via Non-Convex Matrix Factorization, Efficiently and Provably Dohyung Park Anastasios Kyrillidis Constantine Caramanis Sujay Sanghavi 166 55 0 10 Jun 2016
Provable Burer-Monteiro factorization for a class of norm-constrained matrix problems Dohyung Park Anastasios Kyrillidis Srinadh Bhojanapalli Constantine Caramanis Sujay Sanghavi 222 22 0 04 Jun 2016
High Dimensional Multivariate Regression and Precision Matrix Estimation via Nonconvex Optimization Jinghui Chen Quanquan Gu 120 0 0 02 Jun 2016
Fast Algorithms for Robust PCA via Gradient Descent Xinyang Yi Dohyung Park Yudong Chen Constantine Caramanis 229 273 0 25 May 2016
$Parameter recovery in two-component contamination mixtures: the $\mathbb{L}^2$ strategy$ Parameter recovery in two-component contamination mixtures: the $\mathbb{L}^2$ strategy S. Gadat J. Kahn C. Marteau C. Maugis-Rabusseau 225 10 0 01 Apr 2016
Nonparametric mixture of Gaussian graphical models Kevin H. Lee Lingzhou Xue 149 2 0 31 Dec 2015
Sharp Computational-Statistical Phase Transitions via Oracle Computational Model Zhaoran Wang Quanquan Gu Han Liu 205 12 0 30 Dec 2015
Statistical and Computational Guarantees for the Baum-Welch Algorithm Fanny Yang Sivaraman Balakrishnan Martin J. Wainwright 155 47 0 27 Dec 2015
Regularized EM Algorithms: A Unified Framework and Statistical Guarantees Xinyang Yi Constantine Caramanis 236 89 0 27 Nov 2015
Complete Dictionary Recovery over the Sphere I: Overview and the Geometric Picture Ju Sun Qing Qu John N. Wright 257 170 0 11 Nov 2015

Statistical guarantees for the EM algorithm: From population to sample-based analysis

9 August 2014

Sivaraman Balakrishnan

Martin J. Wainwright

Bin Yu

ArXiv (abs)PDF HTML

Papers citing "Statistical guarantees for the EM algorithm: From population to sample-based analysis"

50 / 265 papers shown

Title
Optimal Subspace Estimation Using Overidentifying Vectors via Generalized Method of Moments Jianqing Fan Yiqiao Zhong 96 10 0 08 May 2018
Gradient Descent with Random Initialization: Fast Global Convergence for Nonconvex Phase Retrieval Yuxin Chen Yuejie Chi Jianqing Fan Cong Ma 232 249 0 21 Mar 2018
Hidden Integrality and Semi-random Robustness of SDP Relaxation for Sub-Gaussian Mixture Model Yingjie Fei Yudong Chen 139 5 0 17 Mar 2018
Sharp oracle inequalities for stationary points of nonconvex penalized M-estimatorsIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2018 A. Elsener Sara van de Geer 160 12 0 27 Feb 2018
Functional Gradient Boosting based on Residual Network PerceptionInternational Conference on Machine Learning (ICML), 2018 Atsushi Nitanda Taiji Suzuki 161 28 0 25 Feb 2018
Learning Mixtures of Linear Regressions with Nearly Optimal Complexity Yuanzhi Li Yingyu Liang 198 78 0 22 Feb 2018
Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms Ashok Vardhan Makkuva Sewoong Oh Sreeram Kannan Pramod Viswanath MoE 159 21 0 21 Feb 2018
Robust Estimation via Robust Gradient Estimation Adarsh Prasad A. Suggala Sivaraman Balakrishnan Pradeep Ravikumar 268 223 0 19 Feb 2018
Non-convex Optimization for Machine Learning Prateek Jain Purushottam Kar 322 502 0 21 Dec 2017
On the nonparametric maximum likelihood estimator for Gaussian location mixture densities with application to Gaussian denoising Sujayam Saha Adityanand Guntuboyina 153 56 0 06 Dec 2017
Clustering Semi-Random Mixtures of Gaussians Pranjal Awasthi Aravindan Vijayaraghavan 138 12 0 23 Nov 2017
Parameter Estimation in Gaussian Mixture Models with Malicious Noise, without Balanced Mixing Coefficients Jing Xu Jakub Mareˇcek 109 5 0 21 Nov 2017
Alternating minimization for dictionary learning: Local Convergence Guarantees Niladri S. Chatterji Peter L. Bartlett 168 28 0 09 Nov 2017
On Learning Mixtures of Well-Separated Gaussians O. Regev Aravindan Vijayaraghavan 238 75 0 31 Oct 2017
An Expectation Maximization Framework for Yule-Simon Preferential Attachment Models Lucas Roberts Denisa Roberts 61 1 0 23 Oct 2017
Estimating a network from multiple noisy realizations Can M. Le Keith Levin Elizaveta Levina 184 38 0 13 Oct 2017
Reliable Clustering of Bernoulli Mixture Models Amir Najafi Abolfazl Motahari Hamid R. Rabiee 92 3 0 05 Oct 2017
Maximum likelihood estimation of the Latent Class Model through model boundary decomposition E. Allman H. Cervantes R. Evans Serkan Hocsten Kaie Kubjas Daniela Lemke J. Rhodes Piotr Zwiernik 214 15 0 04 Oct 2017
Community Recovery in Hypergraphs Kwangjun Ahn Kangwook Lee Changho Suh 123 35 0 12 Sep 2017
Learning Mixture of Gaussians with Streaming Data Aditi Raghunathan Ravishankar Krishnaswamy Prateek Jain 154 8 0 08 Jul 2017
An Alternative to EM for Gaussian Mixture Models: Batch and Stochastic Riemannian OptimizationMathematical programming (MP), 2017 Reshad Hosseini S. Sra 117 68 0 10 Jun 2017
Convergence Analysis of Gradient EM for Multi-component Gaussian Mixture Bowei Yan Mingzhang Yin Purnamrita Sarkar 147 1 0 23 May 2017
Solving (most) of a set of quadratic equalities: Composite optimization for robust phase retrieval John C. Duchi Feng Ruan 165 178 0 05 May 2017
Estimating the Coefficients of a Mixture of Two Linear Regressions by Expectation Maximization Jason M. Klusowski Dana Yang W. Brinda 143 44 0 26 Apr 2017
Speeding Up Latent Variable Gaussian Graphical Model Estimation via Nonconvex OptimizationsNeural Information Processing Systems (NeurIPS), 2017 Pan Xu Jian Ma Quanquan Gu CML 114 25 0 28 Feb 2017
Structured signal recovery from quadratic measurements: Breaking sample complexity barriers via nonconvex optimizationIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2017 Mahdi Soltanolkotabi 155 107 0 20 Feb 2017
Rate Optimal Estimation and Confidence Intervals for High-dimensional Regression with Missing CovariatesJournal of Multivariate Analysis (J. Multivar. Anal.), 2017 Yining Wang Jialei Wang Sivaraman Balakrishnan Aarti Singh 162 9 0 09 Feb 2017
Maximum likelihood estimation of determinantal point processes Victor-Emmanuel Brunel Ankur Moitra Philippe Rigollet John C. Urschel 200 11 0 23 Jan 2017
Statistical and Computational Guarantees of Lloyd's Algorithm and its Variants Yu Lu Harrison H. Zhou 424 123 0 07 Dec 2016
Simultaneous Clustering and Estimation of Heterogeneous Graphical Models Botao Hao W. Sun Yufeng Liu Guang Cheng 236 87 0 28 Nov 2016
On the Convergence of the EM Algorithm: A Data-Adaptive Analysis Chong Wu Can Yang Hongyu Zhao Ji Zhu 188 19 0 02 Nov 2016
Convergence rate of stochastic k-means Cheng Tang C. Monteleoni 156 26 0 16 Oct 2016
STORE: Sparse Tensor Response Regression and Neuroimaging Analysis W. Sun Lexin Li 209 97 0 15 Sep 2016
Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences Chi Jin Yuchen Zhang Sivaraman Balakrishnan Martin J. Wainwright Sai Li 191 140 0 04 Sep 2016
Ten Steps of EM Suffice for Mixtures of Two Gaussians C. Daskalakis Christos Tzamos Manolis Zampetakis 599 128 0 01 Sep 2016
Global analysis of Expectation Maximization for mixtures of two GaussiansNeural Information Processing Systems (NeurIPS), 2016 Ji Xu Daniel J. Hsu A. Maleki 430 131 0 26 Aug 2016
Solving a Mixture of Many Random Linear Equations by Tensor Decomposition and Alternating Minimization Xinyang Yi Constantine Caramanis Sujay Sanghavi 117 62 0 19 Aug 2016
A Tight Convex Upper Bound on the Likelihood of a Finite MixtureInternational Conference on Pattern Recognition (ICPR), 2016 Elad Mezuman Yair Weiss 61 1 0 18 Aug 2016
Statistical Guarantees for Estimating the Centers of a Two-component Gaussian Mixture by EM Jason M. Klusowski W. Brinda 128 20 0 07 Aug 2016
Covariate Regularized Community Detection in Sparse GraphsJournal of the American Statistical Association (JASA), 2016 Bowei Yan Purnamrita Sarkar 295 61 0 10 Jul 2016
Finding Low-Rank Solutions via Non-Convex Matrix Factorization, Efficiently and Provably Dohyung Park Anastasios Kyrillidis Constantine Caramanis Sujay Sanghavi 166 55 0 10 Jun 2016
Provable Burer-Monteiro factorization for a class of norm-constrained matrix problems Dohyung Park Anastasios Kyrillidis Srinadh Bhojanapalli Constantine Caramanis Sujay Sanghavi 222 22 0 04 Jun 2016
High Dimensional Multivariate Regression and Precision Matrix Estimation via Nonconvex Optimization Jinghui Chen Quanquan Gu 120 0 0 02 Jun 2016
Fast Algorithms for Robust PCA via Gradient Descent Xinyang Yi Dohyung Park Yudong Chen Constantine Caramanis 229 273 0 25 May 2016
$Parameter recovery in two-component contamination mixtures: the $\mathbb{L}^2$ strategy$ Parameter recovery in two-component contamination mixtures: the $\mathbb{L}^2$ strategy S. Gadat J. Kahn C. Marteau C. Maugis-Rabusseau 225 10 0 01 Apr 2016
Nonparametric mixture of Gaussian graphical models Kevin H. Lee Lingzhou Xue 149 2 0 31 Dec 2015
Sharp Computational-Statistical Phase Transitions via Oracle Computational Model Zhaoran Wang Quanquan Gu Han Liu 205 12 0 30 Dec 2015
Statistical and Computational Guarantees for the Baum-Welch Algorithm Fanny Yang Sivaraman Balakrishnan Martin J. Wainwright 155 47 0 27 Dec 2015
Regularized EM Algorithms: A Unified Framework and Statistical Guarantees Xinyang Yi Constantine Caramanis 236 89 0 27 Nov 2015
Complete Dictionary Recovery over the Sphere I: Overview and the Geometric Picture Ju Sun Qing Qu John N. Wright 257 170 0 11 Nov 2015